Chroma vs Qdrant
Two sides of the vector database decision: embedded / local-first and open-source vector store. When each fits, what it costs, who moves from one to the other, and what makers who chose it say.
Which fits you
Choose Chroma if- You're prototyping retrieval on your laptop, or want vectors in files with no server
Use it whenYou're still figuring out whether retrieval works for your use case.
Trade-offFor production you either run its server yourself or move to Chroma Cloud.
Choose Qdrant if- You need an open-source store with heavy filtering or hybrid search, self-hosted or managed
Use it whenYour queries combine similarity with many filters, such as tenant, date and category.
Trade-offOne more service to deploy and keep in sync with your main database.
At a glance
| Chroma | Qdrant | |
|---|---|---|
| Used by | 13 makers' products · 69 open-source projects | 18 makers' products · 68 open-source projects |
| Cost at default usagevectors stored 1 million vectors, queries 1 million queries, vectors written or updated 500k writes | $51/mo Starter | $103/mo Standard (3 nodes, 0.5 vCPU / 4 GiB each) |
| Moved to it on GitHubpull requests since Oct 2024 | fewer than 3 | 4 from Chroma |
| Downloads | 236.5k/wk−12% vs npm | 696.8k/wk−19% vs npm |
| Pricing | Free and open source to self-host (Apache-2.0); Chroma Cloud is usage-based with free starting credits. · paid from Usage-based | Free and open source to self-host; Qdrant Cloud has a free tier plus usage-based paid plans. · paid from Usage-based, no minimum |
| Free tier | Yes | Yes |
| Open source | Yes · self-hostable | Yes · self-hostable |
Cost as you grow
At 100k vectors Qdrant costs less ($0 vs $1.32); from about 500k vectors Chroma does ($15 vs $68); from about 5M vectors Qdrant does ($410 vs $1,093). They're different kinds of tool — embedded / local-first and open-source vector store — so the prices don't buy the same thing.
The numbers, plan by plan
| Vectors stored (1,536 dimensions, about 6 GB per million) | Chroma | Qdrant |
|---|---|---|
| 0.1 | $1.32 Starter | $0 Free |
| 0.5 | $15 Starter | $68 Standard (1 node, 1 vCPU / 8 GiB) |
| 1 | $51 Starter | $103 Standard (3 nodes, 0.5 vCPU / 4 GiB each) |
| 5 | $1,093 Starter | $410 Standard (3 nodes, 2 vCPU / 16 GiB each) |
| 10 | $4,281 Starter | $820 Standard (3 nodes, 4 vCPU / 32 GiB each) |
| 50 | $105,226 Starter | $4,374 Standard (2 nodes, 32 vCPU / 256 GiB each) |
| 100 | $419,999 Starter | $8,747 Standard (4 nodes, 32 vCPU / 256 GiB each) |
Who moves from one to the other
Public pull requests on GitHub since Oct 2024 whose title says "Chroma to Qdrant" or the reverse — real code changes, by developers in general rather than makers only.
Chroma → Qdrant4 PRs- feat(rag_core): switch retriever backend from Chroma to Qdrant financ…Xeoyeon/Whyfi-v2 · 2026-08-14
- Migrate RAG vector storage from local Chroma to Qdrantseethygerald/myfinancialapp · 2026-05-24
- feat: migrate chroma to qdrantrobbypambudi/RAGforge · 2025-10-08
- Add Chroma DB support as an alternative to Qdranthadv/wisdomforge · 2025-03-27
What makers say
Makers on using it for vector database, from Product Hunt and Starter Story interviews, each linked to the source. Products with a page of their own and fuller notes first.
On ChromaChroma makes it super easy to manage embeddings for AI apps. We love the open-source focus and how quickly it integrates into RAG pipelines.
Jeff (the founder) is incredible - super knowledgeable and I'm super bullish on the direction of the product. Let's go!
Powered memory storage with a dead-simple, blazing-fast open-source vector DB. Far easier to self-host than alternatives.
On QdrantAfter evaluating a bunch of Vector DBs to be our internal vector DB, we finally closed on QDrant because it was the one that scaled the best and had the best price performance ratio
Thanks to Qdrant, we utilize it as a vector database to store our knowledge base and uploaded file data. Our RAG would not be possible without it.
We evaluated a bunch of vector DBs—and Qdrant stood out for its blazing speed, filtering, and hybrid search. It's the unsung hero that lets our AI agents recall and reason across docs, CRMs, and conversations in milliseconds.
Loved and watch-outs
Themes that recur in makers' words and Hacker News comments, each linked to what it summarises.
Chroma- Open source and easy to self-host, with a simple API that gets embeddings stored quickly. PHHN
- Full-text and regex search sit alongside vector search, and collection forking suits changing code. trychroma.comHNHN 2HN 3
- Plugs quickly into RAG pipelines and local-first tools built on LangChain or Ollama. PHHNHN 2HN 3
QdrantWho uses each
Chroma13 makers' products
Clarm
Conduit
Supaboard AI
VoltAgent
AICamp
April
Omniflow
Solver
Superflex
TragWhat makers pair each with
With Chroma
MintlifyWith Qdrant
WiseWorld
Conva.AI
cognee
Lyzr
Trieve
Truelink
Byterover
ZamsNeither quite right?
See the whole vector database decision →
pgvectorInside your databaseApps already on Postgres that want vector search in the same database, joined with normal tables.
PineconeManaged vector storeA fully hosted index with nothing to operate, sized by usage.vs Chroma →vs Qdrant →
WeaviateOpen-source vector storeHybrid search that mixes keyword and vector results, with built-in modules that can create embeddings for you.vs Qdrant →
turbopufferManaged vector storeVery large or many-tenant indexes where storing everything on object storage keeps cost down.vs Chroma →vs Qdrant →